Queue Data Structures Explained: Types, Uses, and Implementation

The First-In-First-Out (FIFO) principle governs queues, which are basic data structures in which the first thing entered is also the first item withdrawn. In a variety of applications, such as operating systems, network protocols, and data processing pipelines, they are crucial for managing and organizing data. In essence, queues are used to build priority queuing systems and manage threads in multithreading. The various kinds of queue data structures, their fundamental functions, implementation, and queue applications will all be covered in this blog.

What is a Queue?

In programming, a queue is a crucial data structure. It is open on both ends and operates according to the FIFO (First In, First Out) principle. At one end of the queue, the back end or tail, data is inserted, while at the other end, the front end or head of the queue, data is deleted.

Real-Life Queue in Data Structure Example

A queue in data structures can be compared to a line of people waiting to buy a ticket at a cinema hall. New individuals join the line at the end, while the person at the front gets the ticket and exits first. Similarly, in a queue data structure, the first data element added will be the first to leave the queue.

Real-life examples of queues include:

• People on an escalator
• Shoppers waiting in a cashier line at a store
• Vehicles queued at a car wash
• Cars exiting through a one-way passage

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Types of Queues in Data Structure

There are four different types of queues in data structures:

• Simple Queue
• Circular Queue
• Priority Queue
• Double-Ended Queue (Deque)

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A Simple Queue is a linear data structure that operates on the First-In-First-Out (FIFO) principle, where elements are inserted at the rear (back) and removed from the front (head).

• It is an ordered collection of comparable data types.
• The queue structure follows the FIFO (First In, First Out) approach.
• To remove a newly added element, all previously added elements must first be deleted.

Applications of Circular Queue

• Resource Allocation: Circular Queues are useful for resource allocation in operating systems to manage resource requests, such as CPU, memory, and I/O devices.
• Batch Processing: Circular Queues handle batch jobs, such as data processing or image rendering, by queuing tasks for sequential execution.
• Message Buffering: They buffer messages in communication systems, ensuring smooth data flow between processes.

Circular Queue

A circular queue is a variation of a simple queue where the last element is connected to the first, creating a circular structure.

• The last node is linked to the first node.
• Also referred to as a Ring Buffer, the nodes are connected end-to-end.
• Insertion occurs at the front of the queue, while deletion happens at the end of the queue.
• Example of a circular queue application: Storing days of the week.

Applications of Circular Queue

• CPU Scheduling: Used in operating systems to manage processes efficiently.
• Data Buffering: Commonly employed in data streaming and buffering applications.
• Simulation Systems: Useful for simulating real-world systems and processes, such as traffic flow control.

Priority Queue

In a priority queue, each node is assigned a predefined priority. Nodes with the lowest priority are removed first, while insertion occurs in the order of their arrival.

Applications of Priority Queue:

• Dijkstra’s shortest path algorithm
• Prim’s algorithm
• Data compression techniques, such as Huffman coding

The diagram below illustrates how an application utilizes a priority queue for managing items consumed by the user.

Priority Queue Applications

• Data Compression: In techniques such as Huffman coding, priority queues are utilized to arrange characters based on their frequency of occurrence, aiding in file size reduction.
• Event Simulation: Priority queues are essential for managing events in simulations, ensuring that events scheduled to occur sooner are processed before those set for later.
• Top-k Elements: They efficiently track the top-k elements from a data stream, providing quick access to the most significant items.

Deque (Double Ended Queue)A double-ended queue, commonly referred to as a deque (pronounced "deck"), is a type of data structure that permits the addition or removal of elements from both the front and rear. This characteristic makes it a flexible choice for various applications. Unlike standard queues that adhere to the FIFO (First In, First Out) principle, deques do not impose this limitation.

Deque Applications

• Undo/Redo Functions: Deques are effective in applications that track user actions, enabling users to navigate backward and forward through their action history.
• Storing Web Browser History: In web browsers, deques facilitate the storage of visited pages, allowing for the addition of new pages and the removal of older ones.
• Graph Traversal: In algorithms such as Breadth-First Search (BFS), deques efficiently manage which nodes to explore next.
• Palindrome Checking: Deques can determine if a word or phrase reads the same forwards and backwards by comparing characters from both ends.

Basic Queue Operations in Queue Data Structure

Below are the basic queue operations in data structure: 

Now, let’s explore the two main operations associated with the Queue data structure: enqueue and dequeue.

Enqueue Operation

Here are the steps to enqueue (insert) data into a queue:

1. Check if the queue is full.
2. If the queue is full, display an overflow error and terminate the program.
3. If the queue is not full, increment the rear pointer to indicate the next available space.
4. Add the element at the position indicated by the rear pointer.
5. Return a success message.

Algorithm for Enqueue Operation

procedure enqueuer (data) 
 if queue is full

 return overflow 
 endif

  rear ← rear + 1 
queue[rear] ← data

 return true 
end procedure

Dequeue Operation

Here are the steps to perform the dequeue operation:

1. Check if the queue is full.
2. If the queue is empty, display an underflow error and terminate the program.
3. If the queue is not empty, retrieve the data at the position pointed to by the front pointer.
4. Then, increment the front pointer to point to the next available data element.
5. Return a success message.

Algorithm for Dequeue Operation

procedure dequeue 
 if queue is empty

     return underflow 
 end if  data = queue[front]front ← front + 1
 return true
 end procedure

Implementation of Queue

A queue can be implemented in two primary ways:

1. Sequential Allocation: This method uses an array for implementation. A queue implemented with an array can accommodate only a fixed number of elements.
2. Linked List Allocation: This method utilizes a linked list for implementation. A queue implemented with a linked list can hold an unlimited number of elements.

A queue data structure is typically utilized in situations where the FIFO (First In First Out) principle needs to be applied. Here are some of the most common applications of queues in data structures:

• Managing Requests: Queues are used for managing requests to a single shared resource, such as in CPU scheduling and disk scheduling.
• Handling Interrupts: They are essential in managing hardware or real-time system interrupts.
• Website Traffic Management: Queues help manage the flow of traffic on websites.
• Networking: Routers and switches utilize queues to handle data packets efficiently.
• Media Players: Queues maintain the order of songs in a playlist for media players.

Understanding the queue data structure is essential for those looking to enhance their programming and problem-solving abilities. Familiarity with the various types of queues and their implementations enables you to effectively address issues related to task scheduling, resource management, and data processing, among others. Whether you're developing software for operating systems, managing network traffic, or creating efficient algorithms, a solid grasp of queues will empower you to design more effective solutions. We encourage you to delve deeper into this topic and consider enrolling in data structure courses that can provide insights into how queue data structures function and are implemented, equipping you to tackle complex programming challenges and improve your coding skills overall.